The Effect of Training Older Adults in Tai Chi and Compensatory Stepping on Balance Control
Bibliographic record
Abstract
Abstract\nIntroduction: In Canadian society, there is a growing prevalence of older adults and one of the main problems facing this generation today is the risk of falling. Tai Chi (TC) is a martial art that has demonstrated improvements in balance control. It uses a series of fluid movements that engage head, neck and trunk rotation while simultaneously reducing base of support. In addition, it has been demonstrated that training older adults by administering unpredictable perturbations to challenge balance better equips them to react successfully in response to balance perturbations. This study aims to determine the potential balance specific benefits of a 10-week exercise intervention combining elements of TC/Compensatory stepping among older adults.\nMethods: Eleven (11) older adult volunteers aged 65+ participated in a TC/compensatory stepping exercise class delivered 2x/week for one hour. Fifty five (55) minutes of each class were devoted to practicing TC and 5 minutes for compensatory stepping training. Compensatory stepping training involved the delivery of controlled manual perturbations in either the anterior/posterior or medial/lateral direction. Measures of functional balance included the Berg Balance Scale (BBS) and Timed-Up-And-Go (TUG). Balance confidence was measured using the Activities-Specific Balance Confidence Scale (ABC). Medilogic pressure insoles and Optotrak technology were used during quiet standing, static self-perturbation and gait termination trials to measure balance via maximum excursion, range and root mean square (RMS) values of the centre of pressure (COP) and centre of mass (COM) individually and their interaction. The intervention group underwent testing at baseline, 5 weeks, 10 weeks and 12 weeks post-intervention. A control group of 8 older adult volunteers were tested at the same 0, 5, and 10-week intervals.\nResults: Significant improvements in balance confidence were demonstrated from baseline to week 10 for the intervention group as denoted by scores on the ABC, whereas the control group showed no significant change in balance confidence over time. Functional balance, as measured by the BBS and TUG, also showed significant improvements from baseline to week 10 for the intervention group, where performance was shown to decrease after 12 weeks post-intervention.\nThe intervention group showed significant improvements for measures of quiet standing with eyes open from baseline to week 10 for the intervention group in the categories of anterior-posterior (AP) net COP range and root mean square (RMS), and COM RMS as well as medial-lateral (ML) COP RMS and COM range. The control group did not show any significant changes over time. When eyes were closed, the intervention group saw decreases in AP COP net range and RMS and COM RMS, ML net COP and COM range from baseline to week 10. The control group also demonstrated decreases in AP COP and COM RMS from baseline to week 10. The intervention group demonstrated decreases across time for arm raise perturbation in AP COP and COM range and RMS, as well as the maximum difference between the COP and COM. ML decreases were noted for the intervention group in COP and COM range and for the control group in COM RMS. Lastly, decreases across time for gait termination measures were found for the intervention group in AP net COP range, ML net COP RMS and COM RMS. The control group decreased in ML COP and COM RMS over time.\n \nDiscussion and Conclusion: The intervention group demonstrated significant improvements across time in balance confidence and functional balance as measured by the Activities-Specific Balance Confidence Scale, the Berg Balance Scale and the Timed-Up-and-Go. Inconsistent, yet significant improvements were observed for the intervention group primarily across AP measures of COP and COM range and RMS during quiet standing, arm raise perturbations and gait termination, however some improvements were also found in the ML direction. It is thought that much of these balance improvements were due to an increase in core strength and strength about the ankle joint as well as sensory uptake information from the bottom of the feet brought about by specific balance challenging motions in Tai Chi training. Compensatory stepping training is likely to have enhanced individual’s ability to respond more successfully when faced with an unexpected perturbation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".